Multicentre benchmark of PSMA PET/CT and mpMRI fusion for non-invasive clinically significant prostate cancer diagnosis
Year: 2026
Type: article
Abstract: Clinically significant prostate cancer (csPCa) guides-biopsy and treatment decisions, yet its non-invasive diagnosis remains challenging. The incremental value of PSMA PET/CT beyond multiparametric MRI (mpMRI), and the optimal strategy for multimodal fusion, remain unclear. We established a real-world, multicentre benchmark using 527 patients from three hospitals with fully paired PSMA PET, CT, T2-weighted MRI, and diffusion-weighted imaging (DWI), together with pathology-confirmed biopsy labels. Models were developed in one centre ( n = 363) and independently evaluated in two external centres ( n = 164). We compared frozen pretrained encoders, fine-tuned 2D and 3D CNN and Vision Transformer models, three fusion strategies, and an interpretable cross-modal Transformer. PSMA PET provided the greatest incremental value, with its removal producing the largest AUC reduction internally (−0.077) and externally (−0.055), supported by the highest attention attribution (αPET = 0.45). PSMA PET/CT also outperformed mpMRI externally (AUC 0.753 vs. 0.653). DWI was the principal source of domain shift, as its exclusion improved external AUC by 0.079 amid inter-centre b-value heterogeneity. Intermediate fusion performed most consistently internally, whereas late fusion and pretrained 2D models generalised better externally. This benchmark supports robust, non-invasive csPCa diagnosis by identifying modalities and fusion strategies that generalise reliably across institutions.
Source: npj Digital Medicine
Institutions: University of Cambridge, Central South University, Xiangya Hospital Central South University, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, King's College London, Shandong University, Qilu Hospital of Shandong University, National University of Singapore
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,090
OpenAlex ID: W7223665626
